Many healthcare providers are aware that to drive performance improvement, they need to have the right people and processes in place. In this article we will examine the role technology plays in antimicrobial stewardship (AMS) programs.
Throughout the Back to AMS Basics series, we discussed the key components of an antimicrobial stewardship program, as recommended by the CDC Core Elements and SHEA/IDSA guidelines. Collectively, both documents recommend having the people, processes, and technology in place to ensure success.
Simplifying data collection for AMS programs
Technology is pivotal in automating data collection and reporting for AMS programs in hospitals, significantly enhancing their efficiency and effectiveness. One of the primary ways technology aids these programs is through the integration of electronic health records (EHRs) and standardizing the various elements in the patient records. Patient-specific data, such as antibiotic prescribed, dosages, durations, and microbiology laboratory results, can provide valuable insights. This data can be analyzed to identify patterns and trends in antibiotic use, helping healthcare providers make informed decisions about prescribing practices.
A significant challenge to many AMS programs is balancing the need to collect and analyze data and the actual conducting of interventions at the patient's bedside. In this age of evidence-based medicine, AMS leaders should leverage data to inform their strategies and measure results. However, the time and effort required to extract insights from the data hidden in the EHR are so significant that many AMS leaders spend more time tied to their desks than being out on the patient floor taking care of patients or talking with prescribers to provide education.
Real-time data insight accelerates performance improvement
Contemporary data analytics and machine learning algorithms can also be used to analyze the vast data collected. Historically, hospitals examine their data monthly and quarterly to discern if a problematical pattern is present. Using machine learning, hospitals and AMS leaders can receive real-time alerts as the pattern is emergent. For example, waiting until the quarter end to observe an increase in the usage of antimicrobials with activity against carbapenem-resistant Enterobacterales may be too late for meaningful real-time interventions.
Robust analytics, such as those in Sentri7’s antimicrobial dashboard, can detect anomalies in antimicrobial prescribing, as measured by Days of Therapy (DOT), and notify the AMS leaders of potential issues before becoming problematic. After receiving real-time notifications, AMS leaders can investigate the antimicrobial use in real time and examine the patients’ microbiology results to determine if prescribing restrictions or more stringent infection prevention and control measures are needed to prevent the spread of drug-resistant organisms.
In this series, we discussed the utility of collecting the indication of an antimicrobial prescription as part of a computerized provider order entry. Clinical decision support systems can compare the antimicrobial order with national guidelines, patient-specific microbiology data, local resistance data, patient organ function, and potential drug-drug interactions to ensure that the most appropriate drug, dose, and route are selected before the patient receives the first dose of therapy. Automating this type of prescriber feedback also reduces the time patients receive inappropriate therapy.
Furthermore, collating the indications with antimicrobial utilization enables AMS leaders to have higher visibility on how antimicrobials are used without conducting patient-level Medication Use Evaluation (MUEs). While MUEs remain useful and are considered one of the most accurate measurements of whether antimicrobials are used appropriately, the time and effort required limit how often they can be deployed and, as such, reduce the scope of inquiries. By using higher level assessment to screen for potential problems, AMS leaders can use analytics to select the one or two antimicrobials that warrant the MUE process in any given month or quarter.
Maintaining regulatory compliance
Certified technology is a required component to satisfy regulatory measures. In 2024, the Medicare Promoting Interoperability program added new requirements for the reporting of Antimicrobial Use (AU) and Antimicrobial Resistant (AR) data to the National Healthcare Safety Network (NHSN). Some metrics, such as Days Present and AR event inclusion, are complex and challenging to tabulate; NHSN would not accept manual submission. AMS leaders must use technology vendors who have passed the Synthetic Data Set validation process to submit AU and AR data. Furthermore, to obtain credit for the Promoting Interoperability program, the vendor must be listed on the ONC Certified Health IT Product List.
Technology can significantly increase the efficiency of your AMS program by automating data collection and analysis, reducing the time to action, and maintaining regulatory compliance that may significantly impact financial performance. These technological innovations improve the speed and efficiency of data standardization and management and unlock valuable insights sooner for AMS leaders. While hurdles exist for initially establishing the interfaces and learning the technology platforms, once implemented, AMS leaders can quickly realize the benefits and support the goal of optimizing antibiotic use and combating antimicrobial resistance.
